Description:

Analyze existing data landscapes, data flows, and scientific data sources in the life sciences sector.
Develop enterprise-wide data models for lab, research, and operational data as well as central data products.
Establish semantic data models, metadata standards, and data classifications to enhance data usage and discoverability.
Implement and advance FAIR Data Principles and scientific data standards.
Design modern data platforms based on Snowflake and AWS, developing cross-domain data architectures.
Collaborate closely with labs, R&D, IT, and Data Science to support analytics, AI, and data science applications through harmonized data structures.

Requirements:

Completed degree in Computer Science, Data Science, Bioinformatics, Mathematics, Natural Sciences, or a related field.
Minimum of eight years of professional experience in Data Architecture, Data Modeling, or Enterprise Data Management, with experience in pharmaceutical, biotechnology, diagnostics, or laboratory environments.
Strong knowledge of modern data architectures, data platforms, and data modeling, with practical experience in Snowflake, AWS, and SQL.
Familiarity with concepts such as FAIR Data Principles, Data Mesh, Data Products, Metadata Management, and Data Governance.
Experience with semantic layers, ontologies, and scientific data models for harmonizing complex research and lab data.
Ideally, knowledge in Scientific Informatics, Laboratory Informatics, or the Allotrope Framework (AFO, ASM, ADM, ADF).

Talent Management – career development opportunities.
Work-Life Balance – flexible working hours and remote work options.
Fit and Relaxed – access to EGYM Wellpass.
Enjoy Biking – company bike leasing available.
Green Mobility – discounted travel options.
IT Communities – knowledge exchange, development, and networking with colleagues.
Permanent employment contract, corporate benefits, and team events.

Skills

Benefits